COVID-19 Data From Pakistan

Number of Confirmed, Death and Recovered cases every day across the Pakistan

@kaggle.arslanali4343_covid19_data_from_pakistan

Table List

1 table(167.96 KB)

Pakistan

@kaggle.arslanali4343_covid19_data_from_pakistan.pakistan

167.96 KB
949 rows
67 columns

iso_code Iso Code	continent Continent	location Location	date Date	total_cases Total Cases	new_cases New Cases	new_cases_smoothed New Cases Smoothed	total_cases_per_million Total Cases Per Million	new_cases_per_million New Cases Per Million	new_cases_smoothed_per_million New Cases Smoothed Per Million	tests_units Tests Units	stringency_index Stringency Index	population Population	population_density Population Density	median_age Median Age	aged_65_older Aged 65 Older	aged_70_older Aged 70 Older	gdp_per_capita Gdp Per Capita	extreme_poverty Extreme Poverty	cardiovasc_death_rate Cardiovasc Death Rate	diabetes_prevalence Diabetes Prevalence	female_smokers Female Smokers	male_smokers Male Smokers	handwashing_facilities Handwashing Facilities	hospital_beds_per_thousand Hospital Beds Per Thousand	life_expectancy Life Expectancy	human_development_index Human Development Index
PAK	Asia	Pakistan	Tue Feb 25 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	2	2		0.009	0.009		nan	19.44	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Wed Feb 26 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	2			0.009			nan	19.44	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Thu Feb 27 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	2			0.009			nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Fri Feb 28 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	4	2		0.017	0.009		nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Sat Feb 29 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	4			0.017			nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Sun Mar 01 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	4		0.571	0.017		0.002	nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Mon Mar 02 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	5	1	0.714	0.022	0.004	0.003	nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Tue Mar 03 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	5		0.429	0.022		0.002	nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Wed Mar 04 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	5		0.429	0.022		0.002	nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557
PAK	Asia	Pakistan	Thu Mar 05 2020 00:00:00 GMT+0000 (Coordinated Universal Time)	6	1	0.571	0.026	0.004	0.002	nan	28.7	231402116	255.573	23.5	4.495	2.78	5034.708	4	423.031	8.35	2.8	36.7	59.607	0.6	67.27	0.557


CREATE TABLE pakistan (
  "iso_code" VARCHAR,
  "continent" VARCHAR,
  "location" VARCHAR,
  "date" TIMESTAMP,
  "total_cases" BIGINT,
  "new_cases" BIGINT,
  "new_cases_smoothed" DOUBLE,
  "total_deaths" DOUBLE,
  "new_deaths" DOUBLE,
  "new_deaths_smoothed" DOUBLE,
  "total_cases_per_million" DOUBLE,
  "new_cases_per_million" DOUBLE,
  "new_cases_smoothed_per_million" DOUBLE,
  "total_deaths_per_million" DOUBLE,
  "new_deaths_per_million" DOUBLE,
  "new_deaths_smoothed_per_million" DOUBLE,
  "reproduction_rate" DOUBLE,
  "icu_patients" VARCHAR,
  "icu_patients_per_million" VARCHAR,
  "hosp_patients" VARCHAR,
  "hosp_patients_per_million" VARCHAR,
  "weekly_icu_admissions" VARCHAR,
  "weekly_icu_admissions_per_million" VARCHAR,
  "weekly_hosp_admissions" VARCHAR,
  "weekly_hosp_admissions_per_million" VARCHAR,
  "total_tests" DOUBLE,
  "new_tests" DOUBLE,
  "total_tests_per_thousand" DOUBLE,
  "new_tests_per_thousand" DOUBLE,
  "new_tests_smoothed" DOUBLE,
  "new_tests_smoothed_per_thousand" DOUBLE,
  "positive_rate" DOUBLE,
  "tests_per_case" DOUBLE,
  "tests_units" VARCHAR,
  "total_vaccinations" DOUBLE,
  "people_vaccinated" DOUBLE,
  "people_fully_vaccinated" DOUBLE,
  "total_boosters" DOUBLE,
  "new_vaccinations" DOUBLE,
  "new_vaccinations_smoothed" DOUBLE,
  "total_vaccinations_per_hundred" DOUBLE,
  "people_vaccinated_per_hundred" DOUBLE,
  "people_fully_vaccinated_per_hundred" DOUBLE,
  "total_boosters_per_hundred" DOUBLE,
  "new_vaccinations_smoothed_per_million" DOUBLE,
  "new_people_vaccinated_smoothed" DOUBLE,
  "new_people_vaccinated_smoothed_per_hundred" DOUBLE,
  "stringency_index" DOUBLE,
  "population" BIGINT,
  "population_density" DOUBLE,
  "median_age" DOUBLE,
  "aged_65_older" DOUBLE,
  "aged_70_older" DOUBLE,
  "gdp_per_capita" DOUBLE,
  "extreme_poverty" BIGINT,
  "cardiovasc_death_rate" DOUBLE,
  "diabetes_prevalence" DOUBLE,
  "female_smokers" DOUBLE,
  "male_smokers" DOUBLE,
  "handwashing_facilities" DOUBLE,
  "hospital_beds_per_thousand" DOUBLE,
  "life_expectancy" DOUBLE,
  "human_development_index" DOUBLE,
  "excess_mortality_cumulative_absolute" VARCHAR,
  "excess_mortality_cumulative" VARCHAR,
  "excess_mortality" VARCHAR,
  "excess_mortality_cumulative_per_million" VARCHAR
);